Data Science Basic Principles Ideas Focus on actionable patterns Build predictive models-supervised learning(train test, x-validate) Avoid overfitting Calculating similarity of objects -unsupervised learning Avoid information leakers Select important variables/features Model accuracy vs lift: how much more prevalent a pattern is than would be expected by chance Estimate probability and cost/gain of actions lelp optimize decisions o KDnuggets 2013Data Science Basic Principles & Ideas • Focus on actionable patterns • Build predictive models - supervised learning (train, test, x-validate) • Avoid overfitting • Calculating similarity of objects - unsupervised learning • Avoid information leakers • Select important variables/features • Model accuracy vs lift: how much more prevalent a pattern is than would be expected by chance • Estimate probability and cost/gain of actions • Help optimize decisions © KDnuggets 2013 13